What are the common threats in modeling?

What are the common threats in modeling?

Common threats in modeling include data bias, overfitting, underfitting, and lack of interpretability.

Can you explain data bias and how it affects models?

Data bias occurs when the training data is not representative of the real-world scenario, leading to skewed predictions.

What is overfitting and how can I avoid it?

Overfitting happens when a model learns the training data too well, capturing noise instead of the underlying pattern. You can avoid it by using techniques like cross-validation and regularization.

Are there any tools to help identify these threats?

Yes, tools like SHAP and LIME can help identify bias and interpretability issues in your models.